📇 Rhumatologue · BOURGOIN JALLIEU CEDEX · (38) · Salarié
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The bone & joint journal · 2016
AimsAn evidence-based radiographic Decision Aid for meniscal-bearing unicompartmental knee arthroplasty (UKA) has been developed and this study investigates its performance at an independent centre.Patients and MethodsPre-operative radiographs, including stress views, from a consecutive cohort of 550 knees undergoing arthroplasty (UKA or total knee arthroplasty; TKA) by a single-surgeon were assessed. Suitability for UKA was determined using the Decision Aid, with the assessor blinded to treatment received, and compared with actual treatment received, which was determined by an experienced UKA surgeon based on history, examination, radiographic assessment including stress radiographs, and intra-operative assessment in line with the recommended indications as described in the literature.ResultsThe sensitivity and specificity of the Decision Aid was 92% and 88%, respectively. Excluding knees where a clear pre-operative plan was made to perform TKA, i.e. patient request, the sensitivity was 93% and specificity 96%. The false-positive rate was low (2.4%) with all affected patients readily identifiable during joint inspection at surgery. In patients meeting Decision Aid criteria and receiving UKA, the five-year survival was 99% (95% confidence intervals (CI) 97 to 100). The false negatives (3.5%), who received UKA but did not meet the criteria, had significantly worse functional outcomes (flexion p < 0.001, American Knee Society Score - Functional p < 0.001, University of California Los Angeles score p = 0.04), and lower implant survival of 93.1% (95% CI 77.6 to 100).ConclusionThe radiographic Decision Aid safely and reliably identifies appropriate patients for meniscal-bearing UKA and achieves good results in this population. The widespread use of the Decision Aid should improve the results of UKA. Cite this article: Bone Joint J 2016;98-B(10 Suppl B):3–10.
PloS one · 2025
Background Osteoarthritis affects about 528 million people worldwide, causing pain and stiffness in the joints. Arthroplasty is commonly performed to treat joint osteoarthritis, reducing pain and improving mobility. Nevertheless, a significant share of patients remain unsatisfied with their surgery. Personalised arthroplasty was introduced to improve surgical outcomes however current solutions require delays, making it difficult to integrate in clinical routine. We propose a fully automated workflow to design patient-specific implants for total knee arthroplasty. Methods The proposed pipeline first uses artificial neural networks to segment the femur and tibia proximal and distal extremities. Then the full bones are reconstructed using augmented statistical shape models, combining shape and landmarks information. Finally, 77 morphological parameters are computed to design patient-specific implants. The developed workflow has been trained on 91 CT scans and evaluated on 41 CT scans, in terms of accuracy and execution time. Results The workflow accuracy was 0.4±0.2mm for segmentation, 1.0±0.3mm for full bone reconstruction, and 2.2±1.5mm for anatomical landmarks determination. The custom implants fitted the patients’ anatomy with 0.9±0.5mm accuracy. The whole process from segmentation to implants’ design lasted about 15 minutes. Conclusion The proposed workflow allows the establishment of a patient-specific pre-operative planning in a very short time, making it easily available for all patients. It performs a fast and reliable personalisation of knee implants, including CT segmentation, bone modelling, morphological analysis and implant design, without requiring any manual intervention. Combined with efficient implant manufacturing techniques, this solution could help answer the growing number of arthroplasties while reducing complications and improving patients’ satisfaction.
European journal of endocrinology · 2024
Abstract Background Osteoporosis (OP) is a pathology characterized by bone fragility affecting 30% of postmenopausal women, mainly due to estrogen deprivation and increased oxidative stress. An autophagy involvement is suspected in OP pathogenesis but a definitive proof in humans remains to be obtained. Methods Postmenopausal women hospitalized for femoral neck fracture (OP group) or total hip replacement (Control group) were enrolled using very strict exclusion criteria. Western blot was used to analyze autophagy level. Results The protein expression level of the autophagosome marker LC3-II was significantly decreased in bone of OP patients relative to the control group. In addition, the protein expression of the hormonally upregulated neu-associated kinase (HUNK), which is upregulated by female hormones and promotes autophagy, was also significantly reduced in bone of the OP group. Conclusions These results demonstrate for the first time that postmenopausal OP patients have a deficit in bone autophagy level and suggest that HUNK could be the factor linking estrogen loss and autophagy decline. Clinical trial registration number ClinicalTrials.gov Identifier: NCT03175874, 2/6/2017.
Source PubMed · Recherche par auteur (homonymes possibles, vérifier l'affiliation).
PloS one · 2025 · Journal Article
Guezou-Philippe A, Clavé A, Maguet E, Maintier L, et al.
European journal of endocrinology · 2024 · Journal Article
Trojani MC, Clavé A, Bereder I, Camuzard O, et al.
The bone & joint journal · 2016 · Journal Article
Hamilton TW, Pandit HG, Lombardi AV, Adams JB, et al.